At a Glance
- Tasks: Build AI agents to assist scientists in research planning and execution.
- Company: Join EIT's innovative AI and Robotics team.
- Benefits: Enjoy enhanced holiday pay, private medical insurance, and a supportive work environment.
- Other info: Collaborative culture that values creativity, emotional intelligence, and career growth.
- Why this job: Make a real impact in scientific research with cutting-edge AI technology.
- Qualifications: Experience in software development and integrating tools for scientific applications.
The predicted salary is between 63000 - 77000 £ per year.
Join EIT's AI and Robotics team to build AI agents that help scientists plan and carry out research. Our LifeAI platform connects models, scientific tools, data and compute so researchers can investigate questions, run analyses and review results.
You will build agent skills, tool integrations and evaluations, initially for protein design and enzyme engineering. Your work will help agents propose workflows, explain their assumptions, execute reviewed plans and produce candidates and evidence for experimental testing.
Reporting to the Lead Software Engineer, you will work with scientific product managers, researchers and platform teams. You will build on EIT's existing agent framework and scientific tools, with programme scientists providing domain guidance and scientific review. This is a hands-on engineering role focused on making AI useful in research.
Key Responsibilities
- Turn scientific objectives and constraints into agent instructions, tool inputs and candidate checks, working with scientists and product managers.
- Build agent workflows that retrieve relevant evidence, propose design steps and explain assumptions, uncertainties and decisions requiring scientific review.
- Integrate scientific tools, models and calculators; validate inputs, interpret outputs and handle failures.
- Connect workflows to data storage, compute, approval and progress-reporting capabilities, working with the data and platform teams.
- Implement candidate generation, filtering and ranking against agreed criteria. Prepare sequences and supporting results for scientist review and experimental testing, including gene synthesis where required.
- Build workflow-specific reference cases and regression checks using shared evaluation tooling.
- Compare permitted models and configurations for task quality, completion, speed and cost.
- Investigate failures in reasoning, tool use and execution; improve agent instructions, context handling and code using evaluation results and scientist feedback.
- Record input references, tool and model versions, parameters and output locations so results can be inspected and reproduced.
- Write tested, maintainable code, contribute to reviews and support deployed workflows. Reuse components as scientific programmes expand.
Essential Knowledge, Skills, and Experience
If you meet most of these, we'd like to hear from you.
- You have shipped multi-step agentic workflows with tool integrations and context management.
- You have built reusable agent skills or tool interfaces, for example with MCP.
- You write APIs and data-handling code with automated tests and version control.
- You have integrated tools or services and handled invalid inputs, asynchronous execution and partial failures.
- You can turn examples and failure cases into repeatable evaluations. You use evaluation results to change how an agent behaves, not just to report on it.
- You can work with domain experts and turn unfamiliar requirements into testable software.
Desirable Knowledge, Skills, and Experience
These are optional; you do not need to meet them to apply.
- Familiarity with protein design, enzyme engineering, computational biology or scientific software.
- Experience integrating sequence or structure analysis, molecular modelling or protein-design tools.
- Experience with literature retrieval, evidence-linked reporting or scientific data formats.
- Familiarity with workflow engines, containers, cloud or HPC compute, and data-access controls.
Benefits
We offer the following salary and benefits: Enhanced holiday pay, Pension, Life Assurance, Income Protection, Private Medical Insurance, Hospital Cash Plan, Therapy Services, Perk Box, Electric Car Scheme.
At the Ellison Institute, we believe a collaborative, inclusive team is key to our success. We are building a supportive environment where creative risks are encouraged, and everyone feels heard. Valuing emotional intelligence, empathy, respect, and resilience, we encourage people to be curious and to have a shared commitment to excellence. Join us and make an impact!
AI Engineer in Oxford employer: Ellison Institute of Technology
At the Ellison Institute of Technology (EIT), we pride ourselves on being an exceptional employer, fostering a culture of innovation and collaboration in the heart of Oxford. Our commitment to employee growth is evident through access to state-of-the-art facilities and opportunities to work alongside world-class researchers, enabling you to contribute to groundbreaking advancements in plant science and sustainable agriculture. With a comprehensive benefits package, including enhanced holiday allowances and private medical insurance, EIT is dedicated to supporting your well-being while you make a meaningful impact on global challenges.
Contact Details:
Ellison Institute of Technology Recruitment Team
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Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
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How to prepare for a job interview at Ellison Institute of Technology
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
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Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Ellison Institute of Technology uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
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Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
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